MRI-based risk stratification for clinically significant prostate cancer detection at biopsy: The value of zonal-specific PSA density and PSHS

  • 0Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland.

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Summary

This summary is machine-generated.

Combining prostate-specific antigen density (PSAD) variants with the Prostate Signal Intensity Homogeneity Score (PSHS) improves clinically significant prostate cancer (csPCa) detection. Specifically, transition zone PSAD (PSAD-TZ) and PSHS enhance risk stratification for biopsy decisions.

Area Of Science

  • Radiology
  • Urology
  • Oncology

Background

  • Multiparametric MRI (mpMRI) is crucial for prostate cancer detection.
  • Accurate risk stratification is needed to optimize prostate biopsy selection.
  • Zonal-specific PSA density (PSAD) variants offer potential for improved diagnostic accuracy.

Purpose Of The Study

  • To evaluate zonal-specific PSAD variants (whole-gland, peripheral zone, transition zone) combined with Prostate Signal Intensity Homogeneity Score (PSHS) for detecting clinically significant prostate cancer (csPCa).
  • To enhance risk stratification and patient selection for prostate biopsy.
  • To investigate the combined diagnostic performance of PI-RADS, PSAD-TZ, and PSHS.

Main Methods

  • Retrospective single-center study of 297 patients with suspected prostate cancer undergoing mpMRI and biopsy.
  • Calculation of whole-gland (PSAD-T), peripheral zone (PSAD-PZ), and transition zone (PSAD-TZ) PSA densities from MRI-derived volumes.
  • Assessment of diagnostic performance using ROC analysis and conditional inference trees for PI-RADS, PSAD-TZ, and PSHS.

Main Results

  • csPCa was diagnosed in 126 (42.4%) patients.
  • PSAD-TZ showed superior csPCa prediction performance (AUC 0.78) compared to PSAD-T (AUC 0.75) and PSAD-PZ (AUC 0.63).
  • Patients with PI-RADS ≤ 3 and elevated PSAD-TZ with low PSHS scores (≤3) had an elevated risk of missed csPCa.

Conclusions

  • Integrating PI-RADS, PSAD-TZ, and PSHS improves risk stratification for csPCa detection at biopsy.
  • This combined approach enables more precise identification of high-risk patients requiring further evaluation.
  • It may reduce false-negative MRI results and refine biopsy indication decisions.